Table 2.

Machine-learning model results

	Meta info (sex, age)	Common clinical features	Unique clinical features	AUROC	ACC	PRE	SEN
Name-response			✓	0.72 ± 0.04	0.69 ± 0.04	0.67 ± 0.05	0.77 ± 0.08
Name-response	✓		✓	0.81 ± 0.02	0.73 ± 0.03	0.72 ± 0.03	0.77 ± 0.05
Imitation			✓	0.65 ± 0.00	0.65 ± 0.02	0.64 ± 0.02	0.69 ± 0.02
Imitation		✓	✓	0.75 ± 0.00	0.69 ± 0.06	0.71 ± 0.08	0.69 ± 0.02
Imitation	✓	✓	✓	0.78 ± 0.01	0.74 ± 0.02	0.73 ± 0.02	0.78 ± 0.04
Ball-playing			✓	0.62 ± 0.02	0.55 ± 0.02	0.54 ± 0.02	0.76 ± 0.02
Ball-playing		✓	✓	0.78 ± 0.03	0.69 ± 0.05	0.69 ± 0.09	0.72 ± 0.06
Ball-playing	✓	✓	✓	0.81 ± 0.03	0.75 ± 0.03	0.72 ± 0.03	0.84 ± 0.04
Ensemble		✓	✓	0.80 ± 0.02	0.74 ± 0.02	0.76 ± 0.04	0.77 ± 0.05
Ensemble	✓	✓	✓	0.83 ± 0.01	0.75 ± 0.02	0.76 ± 0.01	0.80 ± 0.02

The mean and standard deviation of each value were calculated.

ACC accuracy, AUROC area under the receiver operating characteristic curve, PRE precision, SEN sensitivity.